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Radon Implicit Field Transform (RIFT): Learning Scenes from Radar
Signals
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2024
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Daqian Bao
Alex SaadâFalcon
Justin Romberg
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PDF
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Rapid Grassmannian Averaging with Chebyshev Polynomials
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2024
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Brighton Ancelin
Alex SaadâFalcon
Kason Ancelin
Justin Romberg
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Decentralized and Privacy-Preserving Learning of Approximate Stackelberg Solutions in Energy Trading Games With Demand Response Aggregators
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2024
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Styliani I. Kampezidou
Justin Romberg
Kyriakos G. Vamvoudakis
Dimitri N. Mavris
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Subspace Tracking with Dynamical Models on the Grassmannian
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2024
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Alex SaadâFalcon
Brighton Ancelin
Justin Romberg
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PDF
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Robust Broadband Beamforming using Bilinear Programming
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2024
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Nakul Singh
Coleman DeLude
Mark A. Davenport
Justin Romberg
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PDF
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Real-time Digital RF Emulation -- II: A Near Memory Custom Accelerator
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2024
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Mandovi Mukherjee
Xiangyu Mao
Nael Mizanur Rahman
Coleman DeLude
J. Driscoll
Sudarshan Sharma
Payman Behnam
Uday Kamal
Jongseok Woo
Daehyun Kim
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Real-time Digital RF Emulation -- I: The Direct Path Computational Model
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2024
|
Coleman DeLude
J. Driscoll
Mandovi Mukherjee
Nael Mizanur Rahman
Uday Kamal
Xiangyu Mao
Sharjeel Khan
Hariharan Sivaraman
Eric Huang
Jeffrey McHarg
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Precise asymptotics of reweighted least-squares algorithms for linear
diagonal networks
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2024
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Chiraag Kaushik
Justin Romberg
Vidya Muthukumar
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PDF
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Natural Policy Gradient and Actor Critic Methods for Constrained
Multi-Task Reinforcement Learning
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2024
|
Sihan Zeng
Thinh T. Doan
Justin Romberg
|
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+
PDF
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A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning
|
2024
|
Sihan Zeng
Thinh T. Doan
Justin Romberg
|
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+
PDF
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Subspace Tracking with Dynamical Models on the Grassmannian
|
2024
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Alex SaadâFalcon
Brighton Ancelin
Justin Romberg
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Confidence-Based Curriculum Learning for Multi-Agent Path Finding
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2024
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Thomy Phan
Joseph A. Driscoll
Justin Romberg
Sven Koenig
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PDF
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Real-time Digital RF Emulation â I: The Direct Path Computational Model
|
2024
|
Coleman DeLude
J. Driscoll
Mandovi Mukherjee
Nahian Rahman
Xun Mao
Uday Kamal
Sharjeel Khan
Hariharan Sivaraman
Eric Huang
Jeffrey C McHarg
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PDF
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Approximately low-rank recovery from noisy and local measurements by convex program
|
2023
|
Kiryung Lee
Rakshith Sharma
Marius Junge
Justin Romberg
|
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Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems
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2023
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Sihan Zeng
Thinh T. Doan
Justin Romberg
|
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+
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Decentralized and Privacy-Preserving Learning of Approximate Stackelberg Solutions in Energy Trading Games with Demand Response Aggregators
|
2023
|
Styliani I. Kampezidou
Justin Romberg
Kyriakos G. Vamvoudakis
Dimitri N. Mavris
|
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+
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PETAL: Physics Emulation Through Averaged Linearizations for Solving Inverse Problems
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2023
|
Jihui Jin
Etienne Ollivier
Richard X. Touret
Matthew McKinley
Karim G. Sabra
Justin Romberg
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Level set methods for gradient-free optimization of metasurface arrays
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2023
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Alex SaadâFalcon
Christopher J. Howard
Justin Romberg
Kenneth W. Allen
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PDF
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Iterative Broadband Source Localization
|
2023
|
Coleman DeLude
Rakshith S. Srinivasa
Santhosh Karnik
Christopher Hood
Mark A. Davenport
Justin Romberg
|
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+
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Slepian Beamforming: Broadband Beamforming using Streaming Least Squares
|
2023
|
Coleman DeLude
Mark A. Davenport
Justin Romberg
|
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+
PDF
Chat
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Optimal Convex Lifted Sparse Phase Retrieval and PCA With an Atomic Matrix Norm Regularizer
|
2022
|
Andrew D. McRae
Justin Romberg
Mark A. Davenport
|
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+
PDF
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Finite-Time Complexity of Online Primal-Dual Natural Actor-Critic Algorithm for Constrained Markov Decision Processes
|
2022
|
Sihan Zeng
Thinh T. Doan
Justin Romberg
|
|
+
PDF
Chat
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Finite-Time Convergence Rates of Decentralized Stochastic Approximation With Applications in Multi-Agent and Multi-Task Learning
|
2022
|
Sihan Zeng
Thinh T. Doan
Justin Romberg
|
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+
PDF
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The United States COVID-19 Forecast Hub dataset
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2022
|
Estee Y. Cramer
Yuxin Huang
Yijin Wang
Evan L Ray
Matthew Cornell
Johannes Bracher
Andrea Brennen
Alvaro J. Castro Rivadeneira
Aaron Gerding
Katie House
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+
PDF
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Finite-Sample Analysis of Two-Time-Scale Natural ActorâCritic Algorithm
|
2022
|
Sajad Khodadadian
Thinh T. Doan
Justin Romberg
Siva Theja Maguluri
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+
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Thomsonâs Multitaper Method Revisited
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2022
|
Santhosh Karnik
Justin Romberg
Mark A. Davenport
|
|
+
PDF
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Streaming Solutions for Time-Varying Optimization Problems
|
2022
|
Tomer Hamam
Justin Romberg
|
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+
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Regularized Gradient Descent Ascent for Two-Player Zero-Sum Markov Games
|
2022
|
Sihan Zeng
Thinh T. Doan
Justin Romberg
|
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+
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Broadband Beamforming via Linear Embedding
|
2022
|
Coleman DeLude
Santhosh Karnik
Mark Davenport
Justin Romberg
|
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+
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A Dual Accelerated Method for Online Stochastic Distributed Averaging: From Consensus to Decentralized Policy Evaluation
|
2022
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Sheng Zhang
Ashwin Pananjady
Justin Romberg
|
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Streaming Reconstruction from Non-uniform Samples
|
2022
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Justin Romberg
|
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+
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Loop Unrolled Shallow Equilibrium Regularizer (LUSER) -- A Memory-Efficient Inverse Problem Solver
|
2022
|
Peimeng Guan
Jihui Jin
Justin Romberg
Mark A. Davenport
|
|
+
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Iterative Broadband Source Localization
|
2022
|
Coleman DeLude
Rakshith Sharma
Santhosh Karnik
Christopher Hood
Mark Davenport
Justin Romberg
|
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+
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Decentralized Feature-Distributed Optimization for Generalized Linear Models.
|
2021
|
Brighton Ancelin
Sohail Bahmani
Justin Romberg
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PDF
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Improved bounds for the eigenvalues of prolate spheroidal wave functions and discrete prolate spheroidal sequences
|
2021
|
Santhosh Karnik
Justin Romberg
Mark A. Davenport
|
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Thomson's Multitaper Method Revisited.
|
2021
|
Santhosh Karnik
Justin Romberg
Mark A. Davenport
|
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+
PDF
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Finite-Time Performance of Distributed Temporal-Difference Learning with Linear Function Approximation
|
2021
|
Thinh T. Doan
Siva Theja Maguluri
Justin Romberg
|
|
+
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A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning
|
2021
|
Sihan Zeng
Thinh T. Doan
Justin Romberg
|
|
+
|
Finite-Time Complexity of Online Primal-Dual Natural Actor-Critic Algorithm for Constrained Markov Decision Processes
|
2021
|
Sihan Zeng
Thinh T. Doan
Justin Romberg
|
|
+
|
Optimal convex lifted sparse phase retrieval and PCA with an atomic matrix norm regularizer
|
2021
|
Andrew D. McRae
Justin Romberg
Mark A. Davenport
|
|
+
|
Streaming Solutions for Time-Varying Optimization Problems
|
2021
|
Tomer Hamam
Justin Romberg
|
|
+
|
Decentralized Feature-Distributed Optimization for Generalized Linear Models
|
2021
|
Brighton Ancelin
Sohail Bahmani
Justin Romberg
|
|
+
|
Approximately low-rank recovery from noisy and local measurements by convex program
|
2021
|
Kiryung Lee
Rakshith Sharma Srinivasa
Marius Junge
Justin Romberg
|
|
+
|
Thomson's Multitaper Method Revisited
|
2021
|
Santhosh Karnik
Justin Romberg
Mark A. Davenport
|
|
+
|
Finite Sample Analysis of Two-Time-Scale Natural Actor-Critic Algorithm
|
2021
|
Sajad Khodadadian
Thinh T. Doan
Justin Romberg
Siva Theja Maguluri
|
|
+
PDF
|
STAN: spatio-temporal attention network for pandemic prediction using real-world evidence
|
2020
|
Junyi Gao
Rakshith Sharma
Cheng Qian
Lucas M. Glass
Jeffrey Spaeder
Justin Romberg
Jimeng Sun
Cao Xiao
|
|
+
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Finite-Time Analysis of Decentralized Stochastic Approximation with Applications in Multi-Agent and Multi-Task Learning.
|
2020
|
Sihan Zeng
Thinh T. Doan
Justin Romberg
|
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+
PDF
Chat
|
Hardware-Aware Pruning of DNNs using LFSR-Generated Pseudo-Random Indices
|
2020
|
Foroozan Karimzadeh
Ningyuan Cao
Brian Crafton
Justin Romberg
Arijit Raychowdhury
|
|
+
PDF
Chat
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Phase retrieval of low-rank matrices by anchored regression
|
2020
|
Kiryung Lee
Sohail Bahmani
Yonina C. Eldar
Justin Romberg
|
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+
PDF
Chat
|
Fast Convergence Rates of Distributed Subgradient Methods With Adaptive Quantization
|
2020
|
Thinh T. Doan
Siva Theja Maguluri
Justin Romberg
|
|
+
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Sample complexity and effective dimension for regression on manifolds
|
2020
|
Andrew D. McRae
Justin Romberg
Mark A. Davenport
|
|
+
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Improved bounds for the eigenvalues of prolate spheroidal wave functions and discrete prolate spheroidal sequences
|
2020
|
Santhosh Karnik
Justin Romberg
Mark A. Davenport
|
|
+
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Localized sketching for matrix multiplication and ridge regression.
|
2020
|
Rakshith Sharma Srinivasa
Mark A. Davenport
Justin Romberg
|
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+
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Convergence Rates of Accelerated Markov Gradient Descent with Applications in Reinforcement Learning
|
2020
|
Thinh T. Doan
Lam M. Nguyen
Nhan H. Pham
Justin Romberg
|
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+
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Fast Convex Pruning of Deep Neural Networks
|
2020
|
Alireza Aghasi
Afshin Abdi
Justin Romberg
|
|
+
PDF
Chat
|
Trading Beams for Bandwidth: Imaging with Randomized Beamforming
|
2020
|
Rakshith Sharma Srinivasa
Mark A. Davenport
Justin Romberg
|
|
+
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Finite-Time Analysis of Stochastic Gradient Descent under Markov Randomness
|
2020
|
Thinh T. Doan
Lam M. Nguyen
Nhan H. Pham
Justin Romberg
|
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+
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A Decentralized Policy Gradient Approach to Multi-task Reinforcement Learning
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2020
|
Sihan Zeng
Aqeel Anwar
Thinh T. Doan
Arijit Raychowdhury
Justin Romberg
|
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+
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Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification
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2020
|
Rakshith Sharma Srinivasa
Cao Xiao
Lucas M. Glass
Justin Romberg
Jimeng Sun
|
|
+
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STAN: Spatio-Temporal Attention Network for Pandemic Prediction Using Real World Evidence
|
2020
|
Junyi Gao
Rakshith Sharma
Cheng Qian
Lucas M. Glass
Jeffrey Spaeder
Justin Romberg
Jimeng Sun
Cao Xiao
|
|
+
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Sample complexity and effective dimension for regression on manifolds
|
2020
|
Andrew D. McRae
Justin Romberg
Mark A. Davenport
|
|
+
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Convex Programming for Estimation in Nonlinear Recurrent Models
|
2020
|
Sohail Bahmani
Justin Romberg
|
|
+
|
Finite-Time Convergence Rates of Decentralized Stochastic Approximation with Applications in Multi-Agent and Multi-Task Learning
|
2020
|
Sihan Zeng
Thinh T. Doan
Justin Romberg
|
|
+
|
Sample complexity and effective dimension for regression on manifolds
|
2020
|
Andrew D. McRae
Justin Romberg
Mark Davenport
|
|
+
|
Improved bounds for the eigenvalues of prolate spheroidal wave functions and discrete prolate spheroidal sequences
|
2020
|
Santhosh Karnik
Justin Romberg
Mark A. Davenport
|
|
+
|
Localized sketching for matrix multiplication and ridge regression
|
2020
|
Rakshith S. Srinivasa
Mark A. Davenport
Justin Romberg
|
|
+
|
Hardware-aware Pruning of DNNs using LFSR-Generated Pseudo-Random Indices
|
2019
|
Foroozan Karimzadeh
Ningyuan Cao
Brian Crafton
Justin Romberg
Arijit Raychowdhury
|
|
+
PDF
Chat
|
Compressive Sampling of Ensembles of Correlated Signals
|
2019
|
Ali Ahmed
Justin Romberg
|
|
+
|
Phase Retrieval of Low-Rank Matrices by Anchored Regression
|
2019
|
Kiryung Lee
Sohail Bahmani
Yonina C. Eldar
Justin Romberg
|
|
+
|
Finite-Time Performance of Distributed Temporal Difference Learning with Linear Function Approximation
|
2019
|
Thinh T. Doan
Siva Theja Maguluri
Justin Romberg
|
|
+
PDF
Chat
|
Fast Compressive Sensing Recovery Using Generative Models with Structured Latent Variables
|
2019
|
Shaojie Xu
Sihan Zeng
Justin Romberg
|
|
+
PDF
Chat
|
A Hardware Realization of Superresolution Combining Random Coding and Blurring
|
2019
|
Kevin Beale
Jianbo Chen
Anthony Giljum
Kevin F. Kelly
Justin Romberg
|
|
+
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Convergence Rates of Distributed TD(0) with Linear Function Approximation for Multi-Agent Reinforcement Learning
|
2019
|
Thinh T. Doan
Siva Theja Maguluri
Justin Romberg
|
|
+
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Trading beams for bandwidth: Imaging with randomized beamforming
|
2019
|
Rakshith Sharma Srinivasa
Mark A. Davenport
Justin Romberg
|
|
+
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Finite-Time Analysis of Distributed TD(0) with Linear Function Approximation for Multi-Agent Reinforcement Learning
|
2019
|
Thinh T. Doan
Siva Theja Maguluri
Justin Romberg
|
|
+
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Convex Programming for Estimation in Nonlinear Recurrent Models
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2019
|
Sohail Bahmani
Justin Romberg
|
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+
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A Reinforcement Learning Framework for Sequencing Multi-Robot Behaviors
|
2019
|
Pietro Pierpaoli
Thinh T. Doan
Justin Romberg
Magnus Egerstedt
|
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+
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Finite-Time Performance of Distributed Two-Time-Scale Stochastic Approximation
|
2019
|
Thinh T. Doan
Justin Romberg
|
|
+
|
Phase Retrieval of Low-Rank Matrices by Anchored Regression
|
2019
|
Kiryung Lee
Sohail Bahmani
Yonina C. Eldar
Justin Romberg
|
|
+
|
Hardware-aware Pruning of DNNs using LFSR-Generated Pseudo-Random Indices
|
2019
|
Foroozan Karimzadeh
Ningyuan Cao
Brian Crafton
Justin Romberg
Arijit Raychowdhury
|
|
+
|
Finite-Time Performance of Distributed Temporal Difference Learning with Linear Function Approximation
|
2019
|
Thinh T. Doan
Siva Theja Maguluri
Justin Romberg
|
|
+
|
Trading beams for bandwidth: Imaging with randomized beamforming
|
2019
|
Rakshith Sharma Srinivasa
Mark A. Davenport
Justin Romberg
|
|
+
|
Accelerating the Convergence Rates of Distributed Subgradient Methods with Adaptive Quantization
|
2018
|
Thinh T. Doan
Siva Theja Maguluri
Justin Romberg
|
|
+
|
Fast Convergence Rates of Distributed Subgradient Methods with Adaptive Quantization
|
2018
|
Thinh T. Doan
Siva Theja Maguluri
Justin Romberg
|
|
+
|
A Hardware Realization of Superresolution Combining Random Coding and Blurring.
|
2018
|
Kevin Beale
Jianbo Chen
Kevin F. Kelly
Justin Romberg
|
|
+
PDF
Chat
|
Solving Equations of Random Convex Functions via Anchored Regression
|
2018
|
Sohail Bahmani
Justin Romberg
|
|
+
|
ROAST: Rapid Orthogonal Approximate Slepian Transform
|
2018
|
Zhihui Zhu
Santhosh Karnik
Michael B. Wakin
Mark A. Davenport
Justin Romberg
|
|
+
|
Fast Convex Pruning of Deep Neural Networks
|
2018
|
Alireza Aghasi
Afshin Abdi
Justin Romberg
|
|
+
|
Fast and Guaranteed Blind Multichannel Deconvolution Under a Bilinear System Model
|
2018
|
Kiryung Lee
Ning Tian
Justin Romberg
|
|
+
|
Distributed Stochastic Approximation for Solving Network Optimization Problems Under Random Quantization
|
2018
|
Thinh T. Doan
Siva Theja Maguluri
Justin Romberg
|
|
+
PDF
Chat
|
Spectral Methods for Passive Imaging: Nonasymptotic Performance and Robustness
|
2018
|
Kiryung Lee
Felix Krahmer
Justin Romberg
|
|
+
|
Fast Convergence Rates of Distributed Subgradient Methods with Adaptive Quantization
|
2018
|
Thinh T. Doan
Siva Theja Maguluri
Justin Romberg
|
|
+
|
A Hardware Realization of Superresolution Combining Random Coding and Blurring
|
2018
|
Kevin Beale
Jianbo Chen
Kevin F. Kelly
Justin Romberg
|
|
+
|
Fast Convex Pruning of Deep Neural Networks
|
2018
|
Alireza Aghasi
Afshin Abdi
Justin Romberg
|
|
+
|
The Eigenvalue Distribution of Discrete Periodic Time-Frequency Limiting Operators
|
2017
|
Zhihui Zhu
Santhosh Karnik
Mark A. Davenport
Justin Romberg
Michael B. Wakin
|
|
+
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Spectral Methods for Passive Imaging: Non-asymptotic Performance and Robustness
|
2017
|
Kiryung Lee
Felix Krahmer
Justin Romberg
|
|
+
PDF
|
The fast Slepian transform
|
2017
|
Santhosh Karnik
Zhihui Zhu
Michael B. Wakin
Justin Romberg
Mark A. Davenport
|
|
+
PDF
Chat
|
Appearance-based gesture recognition in the compressed domain
|
2017
|
Shaojie Xu
Anvesha Amaravati
Justin Romberg
Arijit Raychowdhury
|
|
+
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Anchored Regression: Solving Random Convex Equations via Convex Programming.
|
2017
|
Sohail Bahmani
Justin Romberg
|
|
+
|
Solving Equations of Random Convex Functions via Anchored Regression
|
2017
|
Sohail Bahmani
Justin Romberg
|
|
+
|
Solving Equations of Random Convex Functions via Anchored Regression
|
2017
|
Sohail Bahmani
Justin Romberg
|
|
+
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Spectral Methods for Passive Imaging: Non-asymptotic Performance and Robustness
|
2017
|
Kiryung Lee
Felix Krahmer
Justin Romberg
|
|
+
|
Net-Trim: A Layer-wise Convex Pruning of Deep Neural Networks.
|
2016
|
Alireza Aghasi
Nam Nguyen
Justin Romberg
|
|
+
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Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee
|
2016
|
Alireza Aghasi
Afshin Abdi
Nam Nguyen
Justin Romberg
|
|
+
|
The Fast Slepian Transform
|
2016
|
Santhosh Karnik
Zhihui Zhu
Michael B. Wakin
Justin Romberg
Mark A. Davenport
|
|
+
|
Fast and guaranteed blind multichannel deconvolution under a bilinear system model
|
2016
|
Kiryung Lee
Ning Tian
Justin Romberg
|
|
+
|
Empirical Chaos Processes and Blind Deconvolution
|
2016
|
Ali Ahmed
Felix Krahmer
Justin Romberg
|
|
+
PDF
Chat
|
A Light-powered, "Always-On", Smart Camera with Compressed Domain Gesture Detection
|
2016
|
A. Anvesha
Shaojie Xu
Ningyuan Cao
Justin Romberg
Arijit Raychowdhury
|
|
+
PDF
Chat
|
Near-optimal estimation of simultaneously sparse and low-rank matrices from nested linear measurements
|
2016
|
Sohail Bahmani
Justin Romberg
|
|
+
|
An Overview of Low-Rank Matrix Recovery From Incomplete Observations
|
2016
|
Mark A. Davenport
Justin Romberg
|
|
+
|
Object Learning and Convex Cardinal Shape Composition
|
2016
|
Alireza Aghasi
Justin Romberg
|
|
+
|
Learning Shapes by Convex Composition
|
2016
|
Alireza Aghasi
Justin Romberg
|
|
+
|
Sweep Distortion Removal from THz Images via Blind Demodulation
|
2016
|
Alireza Aghasi
Barmak Heshmat
Albert Redo-Sanchez
Justin Romberg
Ramesh Raskar
|
|
+
|
A Light-powered, Always-On, Smart Camera with Compressed Domain Gesture Detection
|
2016
|
A. Anvesha
Shaojie Xu
Ningyuan Cao
Justin Romberg
Arijit Raychowdhury
|
|
+
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Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation
|
2016
|
Sohail Bahmani
Justin Romberg
|
|
+
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Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee
|
2016
|
Alireza Aghasi
Afshin Abdi
Nam Nguyen
Justin Romberg
|
|
+
|
The Fast Slepian Transform
|
2016
|
Santhosh Karnik
Zhihui Zhu
Michael B. Wakin
Justin Romberg
Mark A. Davenport
|
|
+
|
Empirical Chaos Processes and Blind Deconvolution
|
2016
|
Ali Ahmed
Felix Krahmer
Justin Romberg
|
|
+
|
Learning Shapes by Convex Composition
|
2016
|
Alireza Aghasi
Justin Romberg
|
|
+
|
Fast and guaranteed blind multichannel deconvolution under a bilinear system model
|
2016
|
Kiryung Lee
Ning Tian
Justin Romberg
|
|
+
|
Efficient compressive phase retrieval with constrained sensing vectors
|
2015
|
Sohail Bahmani
Justin Romberg
|
|
+
PDF
Chat
|
Sketching for simultaneously sparse and low-rank covariance matrices
|
2015
|
Sohail Bahmani
Justin Romberg
|
|
+
|
Efficient Compressive Phase Retrieval with Constrained Sensing Vectors
|
2015
|
Sohail Bahmani
Justin Romberg
|
|
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Near-Optimal Estimation of Simultaneously Sparse and Low-Rank Matrices from Nested Linear Measurements
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2015
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Sohail Bahmani
Justin Romberg
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Compressed subspace matching on the continuum
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2015
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William Mantzel
Justin Romberg
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PDF
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Discrete and Continuous-Time Soft-Thresholding for Dynamic Signal Recovery
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2015
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Aurèle Balavoine
Christopher J. Rozell
Justin Romberg
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Compressive Sampling of Ensembles of Correlated Signals
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2015
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Ali Ahmed
Justin Romberg
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Convex Cardinal Shape Composition
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2015
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Alireza Aghasi
Justin Romberg
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PDF
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Lifting for Blind Deconvolution in Random Mask Imaging: Identifiability and Convex Relaxation
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2015
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Sohail Bahmani
Justin Romberg
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PDF
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Convex Cardinal Shape Composition
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2015
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Alireza Aghasi
Justin Romberg
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Efficient Compressive Phase Retrieval with Constrained Sensing Vectors
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2015
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Sohail Bahmani
Justin Romberg
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Compressive Sampling of Ensembles of Correlated Signals
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2015
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Ali Ahmed
Justin Romberg
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Convex Cardinal Shape Composition
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2015
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Alireza Aghasi
Justin Romberg
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PDF
Chat
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Compressive Multiplexing of Correlated Signals
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2014
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Ali Ahmed
Justin Romberg
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Compressed Subspace Matching on the Continuum
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2014
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William Mantzel
Justin Romberg
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Discrete and Continuous-time Soft-Thresholding with Dynamic Inputs
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2014
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Aurèle Balavoine
Christopher J. Rozell
Justin Romberg
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PDF
Chat
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Blind Deconvolution Using Convex Programming
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2014
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Ali Ahmed
Benjamin Recht
Justin Romberg
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Discrete and Continuous-time Soft-Thresholding with Dynamic Inputs
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2014
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Aurèle Balavoine
Christopher J. Rozell
Justin Romberg
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Compressed Subspace Matching on the Continuum
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2014
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William Mantzel
Justin Romberg
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Compressive Multiplexing of Correlated Signals
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2013
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Ali Ahmed
Justin Romberg
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PDF
Chat
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Convergence Speed of a Dynamical System for Sparse Recovery
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2013
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Aurèle Balavoine
Christopher J. Rozell
Justin Romberg
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Sparse Shape Reconstruction
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2013
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Alireza Aghasi
Justin Romberg
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PDF
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Matched Filtering From Limited Frequency Samples
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2013
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Armin Eftekhari
Justin Romberg
Michael B. Wakin
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Sparse Recovery of Streaming Signals Using L1-Homotopy
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2013
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M. Salman Asif
Justin Romberg
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PDF
Chat
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Sparse Shape Reconstruction
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2013
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Alireza Aghasi
Justin Romberg
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Sparse Shape Reconstruction
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2013
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Alireza Aghasi
Justin Romberg
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Compressive Multiplexing of Correlated Signals
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2013
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Ali Ahmed
Justin Romberg
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Blind Deconvolution using Convex Programming
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2012
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Ali Ahmed
Benjamin Recht
Justin Romberg
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Fast and Accurate Algorithms for Re-Weighted L1-Norm Minimization
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2012
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M. Salman Asif
Justin Romberg
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PDF
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Compressive matched-field processing
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2012
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William Mantzel
Justin Romberg
Karim G. Sabra
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PDF
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Convergence and Rate Analysis of Neural Networks for Sparse Approximation
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2012
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Aurèle Balavoine
Justin Romberg
Christopher J. Rozell
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Fast and Accurate Algorithms for Re-Weighted L1-Norm Minimization
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2012
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M. Salman Asif
Justin Romberg
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Blind Deconvolution using Convex Programming
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2012
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Ali Ahmed
Benjamin Recht
Justin Romberg
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Global convergence of the Locally Competitive Algorithm
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2011
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Aurèle Balavoine
Christopher J. Rozell
Justin Romberg
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Sparse signal recovery and dynamic update of the underdetermined system
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2010
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M. Salman Asif
Justin Romberg
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PDF
Chat
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Channel protection: Random coding meets sparse channels
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2009
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M. Salman Asif
William Mantzel
Justin Romberg
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PDF
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Stable signal recovery from incomplete and inaccurate measurements
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2006
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Emmanuel J. Candès
Justin Romberg
Terence Tao
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Stable signal recovery from incomplete observations
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2005
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Emmanuel J. Candès
Justin Romberg
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Practical Signal Recovery from Random Projections
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2005
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Justin Romberg
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